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The High Tech Summit with more than 4,000 attendees took place at the Campus of the Technical University 10-11 October. CeMiSt organized a track on big data in microbial community studies. The track was a total success, full room with many people standing and a panel of speakers from industry and academia

The session was chaired by professor Mikael Rørdam Andersen who contextualized the concept of big data in microbial studies and presented the speakers.

Assistant professor Tammi Vesth from CeMiSt, was the first speaker of the track and explained that most of the data generated corresponds to biological sequences, both DNA and protein. Due to the growing capacity to generate data, researchers have to find a systematic way to store and share for this information to be truly valuable. This is posing future challenges in biological data management, which CeMiSt is currently addressing.

Professor Tilmann Weber also from CeMiSt presented his methodology to mine bacterial genomes in search for new antibiotics. An emergent threat from the overuse of antibiotics is the development of bacterial resistance against them. This is why predicting new genetic cluster that may encode for alternative antibiotics is critical. However, it also requires processing and handling large amounts of sequence data with very variable sequencing quality.

CeMiSt had also the pleasure to welcome two scientists from Novozymes. Dennis Pultz presented a machine learning approach to find desired phenotypes. These algorithms use training datasets of genotypes or genomes responsible for given phenotypes to predict other microorganisms with similar phenotypes. On his part, Michael Roggenbuck showcased a microfluidic platform part of the EU project MetaFluidics to discover previously unknown enzyme activities. Genes isolated from several sources are introduced in bacteria that are further encapsulated and undergo selection cycles based on their enzymatic activity. This enriching process yields a relatively high portion of genes which have the desired activity, but are completely novel in that no similar genes have ever been described to have this function.

Finally the event closed with two speakers on chemistry big data. Starting with Gordon Ross, Mass Spectrometry specialist at Agilent who introduced the audience to mass spectrometry and the challenges to extract and characterize chemical compounds. For example the presence of isotopes, adducts and dimers in samples that may confound the analysis. The session ended with the CeMiSt platform manager Christopher Phippen highlighting the number of natural compounds still to be discovered and how to exploit the chemical space more systematically